Ensemble based uncertainty analysis and its application for hydropower forecasting in cascade reservoir optimal operation

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Wednesday, 7 January 2015
Baoguo Xie, IBM Research, Beijing, China; and M. Zhang, H. Du, and H. wang

The ensemble Kalman filter is introduced to help on improving the forecast skills of rainfall and hydropower output amounts for cascade reservoir system over a major river basin in Southwest China, which includes both the short-term (24h) and mid-term rainfall (120h) forecasts for the optimal operations for the hydropower management, considering reservoirs' daily outputs are highly dependent on the nonlinear and stochastic processes of various weathers. In this study with several event-driven cases during 2014 rainy season, the uncertainty of the rainfall forecasting, is modeled by an ensemble group with multiple predicting members, in which particular uncertain structures have been found during the evolution of the rainfall weathers. And the probabilistic of hydropower outputs in the manner of rainfall uncertainty structure is estimated for the optimal hydropower planning and management.